hpcforge/BubbleML_2

1---2license: cc-by-nc-sa-4.03---4# BubbleML 2.0:5 6**BubbleML_2** is a high-fidelity dataset of boiling simulations in 2D for three fluids (FC-72, Liquid N2 and R515B). It provides paired time-series fields stored in HDF5 (.hdf5) files together with metadata (.json) and explicit train/test splits.7 8---9 10## 🚀 Quickstart11 12The current available dataset subsets are-13```14"single-bubble", "pb-saturated", "pb-subcooled", "fb-velscale", "fb-chf"15```16They are chosen for each individual forecasting task in our paper, viz. Single Bubble, Saturated Pool Boiling, Subcooled Pool Boiling, Flow Boiling- Varying Inlet Velocity and17Flow Boiling- Varying Heat Flux.18```python19from datasets import load_dataset20 21# Load the TRAIN split22ds_train = load_dataset(23    "hpcforge/BubbleML_2",24    name="single-bubble",25    split="train",26    streaming=True,            # to save disk space27    trust_remote_code=True,    # required to run the custom dataset script28)29 30# Load the TEST split31ds_test = load_dataset(32    "hpcforge/BubbleML_2",33    name="single-bubble",34    split="test",35    streaming=True,36    trust_remote_code=True,37)38```39Each example in ds_train / ds_test has the following fields:40  * input41    NumPy array of shape (time_window=5, fields=4, HEIGHT, WIDTH)42  * output43    NumPy array of shape (time_window=5, fields=4, HEIGHT, WIDTH)44  * fluid_params45    List of 9 floats representing: Inverse Reynolds Number, Non-dimensionalized Specific Heat, Non-dimensionalized Viscosity, Non-dimensionalized Density, 46    Non-dimensionalized Thermal Conductivity, Stefan Number, Prandtl Number, Nucleation wait time and the Heater temperature.47    ```48    [inv_reynolds, cpgas, mugas, rhogas, thcogas, stefan, prandtl, heater.nucWaitTime, heater.wallTemp]49    ```50  * filename51    HDF5 filename (e.g. Twall_90.hdf5)